Update modules/visuals.py
Browse files- modules/visuals.py +22 -10
modules/visuals.py
CHANGED
@@ -1,26 +1,31 @@
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import pandas as pd
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def display_dashboard(df: pd.DataFrame):
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st.subheader("π System Summary")
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col1, col2, col3, col4 = st.columns(4)
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col1.metric("Total Poles", df.shape[0])
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col2.metric("π¨ Red Alerts", df[df["Alert_Level__c"] == "Red"].shape[0])
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col3.metric("β‘ Power Issues", df[df["Power_Sufficient__c"] == "No"].shape[0])
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col4.metric("π· Offline Cameras", df[df["Camera_Status__c"] == "Offline"].shape[0])
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import plotly.express as px
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def display_charts(df: pd.DataFrame):
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fig_energy = px.bar(
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df,
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x="Name",
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y=["Solar_Generation__c", "Wind_Generation__c"],
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)
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st.subheader("π¨ Alert Level Breakdown")
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fig_alerts = px.histogram(
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df,
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@@ -29,7 +34,6 @@ def display_charts(df: pd.DataFrame):
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)
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st.plotly_chart(fig_alerts)
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import pydeck as pdk
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# Function to generate heatmap for a given site
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def generate_heatmap_for_site(site_name, df):
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site_df = df[df['Site__c'] == site_name]
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@@ -47,6 +51,9 @@ def generate_heatmap_for_site(site_name, df):
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# Create a color column based on Alert_Level__c
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site_df["color"] = site_df["Alert_Level__c"].map(color_map)
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# Create a Pydeck map for the site
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layer = pdk.Layer(
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"ScatterplotLayer",
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@@ -58,13 +65,18 @@ def generate_heatmap_for_site(site_name, df):
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auto_highlight=True
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)
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view_state = pdk.ViewState(
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latitude=
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longitude=
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zoom=10,
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pitch=40
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)
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tooltip = {
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"html": """
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<b>Pole Name:</b> {Name}<br>
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@@ -80,10 +92,10 @@ def generate_heatmap_for_site(site_name, df):
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}
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}
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# Return the heatmap
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return pdk.Deck(
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map_style="mapbox://styles/mapbox/dark-v10",
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initial_view_state=view_state,
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layers=[layer],
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tooltip=tooltip
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)
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import pandas as pd
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import streamlit as st
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import plotly.express as px
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import pydeck as pdk
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# Function to display system summary metrics
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def display_dashboard(df: pd.DataFrame):
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st.subheader("π System Summary")
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col1, col2, col3, col4 = st.columns(4)
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# Metrics for Total Poles, Red Alerts, Power Issues, Offline Cameras
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col1.metric("Total Poles", df.shape[0])
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col2.metric("π¨ Red Alerts", df[df["Alert_Level__c"] == "Red"].shape[0])
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col3.metric("β‘ Power Issues", df[df["Power_Sufficient__c"] == "No"].shape[0])
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col4.metric("π· Offline Cameras", df[df["Camera_Status__c"] == "Offline"].shape[0])
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# Function to display charts related to energy generation and alert levels
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def display_charts(df: pd.DataFrame):
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# Energy Generation Bar Chart
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fig_energy = px.bar(
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df,
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x="Name",
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y=["Solar_Generation__c", "Wind_Generation__c"],
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title="Energy Generation (Solar vs Wind)"
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)
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st.plotly_chart(fig_energy)
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# Alert Level Breakdown Histogram
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st.subheader("π¨ Alert Level Breakdown")
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fig_alerts = px.histogram(
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df,
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)
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st.plotly_chart(fig_alerts)
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# Function to generate heatmap for a given site
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def generate_heatmap_for_site(site_name, df):
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site_df = df[df['Site__c'] == site_name]
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# Create a color column based on Alert_Level__c
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site_df["color"] = site_df["Alert_Level__c"].map(color_map)
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# Drop rows with missing Longitude or Latitude to avoid errors in the map
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site_df = site_df.dropna(subset=["Longitude__c", "Latitude__c"])
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# Create a Pydeck map for the site
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layer = pdk.Layer(
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"ScatterplotLayer",
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auto_highlight=True
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)
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# Set the view state to center the map on the site
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latitude = site_df["Latitude__c"].mean() if not site_df["Latitude__c"].isnull().all() else 0
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longitude = site_df["Longitude__c"].mean() if not site_df["Longitude__c"].isnull().all() else 0
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view_state = pdk.ViewState(
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latitude=latitude,
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longitude=longitude,
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zoom=10,
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pitch=40
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)
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# Tooltip for when you hover over a pole
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tooltip = {
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"html": """
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<b>Pole Name:</b> {Name}<br>
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}
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}
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# Return the heatmap as a Pydeck map
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return pdk.Deck(
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map_style="mapbox://styles/mapbox/dark-v10",
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initial_view_state=view_state,
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layers=[layer],
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tooltip=tooltip
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)
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